import requests
import datetime
import pandas as pd
import pymysql
from sklearn.preprocessing import MinMaxScaler
from joblib import dump


class WeatherUtils(object):
    """
    天气工具类
    Args:
        object (_type_): _description_
    """

    def __init__(self):
        self.date_list = [
            '2024-07-01',
            '2024-08-01',
            '2024-09-01',
            '2024-10-01',
            '2024-11-01',
            '2024-12-01'
        ]
        self.url = "http://v1.yiketianqi.com/api"

    def get_data(self):
        """
        获取天气数据
        """
        data_list = []
        for d in self.date_list:
            conf = {
                'appid': '382405900',  # 使用自己注册的appid
                'appsecret': 'BA7zIjqn',
               'version': 'history',
                'year': d[:4],
               'month': d[5:7],
                'city': '南昌'
            }
            # 发起请求获取数据
            res = requests.get(self.url + '?', params=conf)
            res_data = res.json()
            # print(res_data)
            for i in res_data['data']:
                data_list.append({
                    'date': datetime.datetime.strptime(i['ymd'], '%Y-%m-%d'),
                    'wendu': i['wendu'],
                    'ywendu': i['ywendu'],
                    'tianqi': i['tianqi'],
                    'fengli': i['fengli'],
                })
        df = pd.DataFrame(data_list)
        df.to_csv('./timing/weather.csv')


class MysqlUtils(object):
    def __init__(self):
        self.conn = pymysql.connect(
            host='127.0.0.1',
            user='root',
            password='root',
            database='scenic',
            port=3306,  # 明确指定端口
            charset='utf8mb4'  # 添加字符集设置
        )
        self.weather_data = pd.read_csv('./timing/weather.csv')

    def is_holiday(self, date):
        """
        是否节假日判断
        """
        if date in ['2024-09-03', '2024-10-01', '2024-10-02', '2024-10-03', '2024-10-04', '2024-10-05', '2024-10-06', '2024-10-07', '2025-01-01', '2025-01-02', '2025-01-03']:
            return 1
        return 0

    def get_data(self):
        cursor = self.conn.cursor(cursor=pymysql.cursors.DictCursor)
        sql = """
        SELECT DATE(g.create_time) as date, count(*) as count FROM order_user_gate_rel g WHERE DATE(g.create_time) < '2025-01-01' GROUP BY date
        """
        cursor.execute(sql)
        res = cursor.fetchall()
        df = pd.DataFrame(res)

        # 合并天气数据
        self.weather_data['date'] = pd.to_datetime(self.weather_data['date'])
        df['date'] = pd.to_datetime(df['date'])
        df = pd.merge(self.weather_data, df, on='date')
        print(df.pivot.head)
        df.pivot.set_index('date', inplace=True)

        df_pivot['dow'] = df_pivot.index.dayofweek  # 星期几（0-6）
        df_pivot['month'] = df_pivot.index.month  # 月份
        df_pivot['is_holiday'] = df_pivot.index.map(self.is_holiday)

        # 打印df_pivot.head
        print(df_pivot.head)

        # 对星期几和月份进行独热编码
        df_pivot = pd.get_dummies(df_pivot, columns=['dow','month', 'tianqi', 'fengli'], dtype=int)

        # 对温度进行转换
        df_pivot['wendu'] = df_pivot['wendu'].str.replace('℃', '').astype(int)
        df_pivot['ywendu'] = df_pivot['ywendu'].str.replace('℃', '').astype(int)

        # 归一化函数
        scaler = MinMaxScaler()
        features = df_pivot[['count']]
        df_pivot['count'] = scaler.fit_transform(features)

        weather_features = df_pivot[['wendu', 'ywendu']]
        dump(scaler, 'timing/scaler.joblib')
        df_pivot[['wendu', 'ywendu']] = scaler.fit_transform(weather_features)
        dump(weather_features, 'timing/weather_features.joblib')

        df_pivot.to_csv('./timing/scenic_data.csv', index=False)


if __name__ == '__main__':
    wu = WeatherUtils()
    wu.get_data()
    mu = MysqlUtils()
    mu.get_data()
